CN116058821A

CN116058821A - User identification method, electronic equipment and body fat scale

Info

Publication number: CN116058821A
Application number: CN202111290102.8A
Authority: CN
Inventors: 彭伟; 王润芝
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-11-02
Filing date: 2021-11-02
Publication date: 2023-05-05

Abstract

The embodiment of the invention provides a user identification method, electronic equipment and a body fat scale. The method comprises the following steps: the body fat scale acquires measurement information of a measured user, wherein the measurement information of the measured user comprises first behavior information; the electronic equipment acquires identification reference information of a user of the electronic equipment, wherein the identification reference information comprises second behavior information; the electronic equipment acquires measurement information of a user to be measured from the body fat scale; the electronic equipment generates a matching result according to the measurement information and the identification reference information, and the matching result is used for representing the probability that the user of the electronic equipment is the tested user; the body fat scale obtains a matching result from at least one electronic device; and judging whether the user of the electronic equipment is a tested user or not according to the matching result of at least one electronic equipment by the body fat scale. According to the embodiment of the invention, the user to be tested is identified through the reference identification information acquired by the electronic equipment and the measurement information acquired by the body fat scale, so that the accuracy of user identification is improved.

Description

User identification method, electronic equipment and body fat scale

[ field of technology ]

The invention relates to the technical field of terminals, in particular to a user identification method, electronic equipment and a body fat scale.

[ background Art ]

With the importance of users on health, body Fat scales (Body Fat scales) are increasingly used in daily life. Body fat scales are commonly shared by multiple people, and when different users use the body fat scales, the users need to be manually switched on the mobile phone so that the mobile phone can receive correct physical sign data of the users, and inconvenience is brought to the users in using the body fat scales.

Compared with the traditional body fat scale, the intelligent wireless fidelity (wireless fidelity, wi-Fi) body fat scale can intelligently identify a user as a household shared body fat scale, and when the user performs weighing, the body fat scale can automatically send measured sign data to an account number of the identified user, so that different users can use the body fat scale conveniently.

Currently, body fat scales are primarily user-identified based on user's vital sign data, which may include, for example, body weight or body fat rate. But the user cannot be accurately identified by using the body weight or body fat rate and other data, so that the accuracy of user identification is low.

[ invention ]

In view of the above, the embodiments of the present invention provide a user identification method, an electronic device, and a body fat scale, which are used for improving accuracy of user identification.

A first aspect provides a user identification method applied to a body fat scale and at least one electronic device, the body fat scale and the at least one electronic device communicating based on a short-range wireless communication protocol;

the method comprises the following steps:

the body fat scale acquires measurement information of a measured user, wherein the measurement information of the measured user comprises first behavior information, and the first behavior information is used for representing the measurement behavior of the measured user detected when the body fat scale measures the physical sign data of the measured user;

the electronic equipment acquires identification reference information of a user of the electronic equipment, wherein the identification reference information comprises second behavior information, and the second behavior information is used for representing the behavior of the user of the electronic equipment;

the electronic equipment acquires measurement information of the tested user from the body fat scale;

the electronic equipment generates a matching result according to the measurement information and the identification reference information, and the matching result is used for representing the probability that a user of the electronic equipment is the tested user;

the body fat scale obtains the matching result from the at least one electronic device;

And the body fat scale judges whether the user of the electronic equipment is the tested user according to the matching result of the at least one electronic equipment.

In one possible implementation manner, the electronic device generates a matching result according to the measurement information and the identification reference information, including:

and the electronic equipment matches the first behavior information with the second behavior information to generate the matching result.

In one possible implementation manner, the measurement information further includes first feature data obtained by the body fat scale measuring the measured user, the identification reference information further includes second feature data, and the electronic device generates a matching result according to the measurement information and the identification reference information, and the method includes:

the electronic device matches the first behavior information with the second behavior information and matches the first feature data with the second feature data to generate the matching result.

In a possible implementation manner, the measurement information further includes first sign data obtained by the body fat scale measuring the measured user, the identification reference information further includes second sign data and a measurement distance, and the measurement distance is a distance between the electronic device and the body fat scale;

The electronic equipment generates a matching result according to the measurement information and the identification reference information, and the matching result comprises the following steps:

the electronic equipment matches the first behavior information with the second behavior information, matches the first sign data with the second sign data, and judges the distance between the user of the electronic equipment and the body fat scale through the measured distance so as to generate the matching result.

In one possible implementation, the first behavior information includes at least one of a scale up period, a first scale up lock period, a first measurement period, or a scale down period.

In one possible implementation manner, the second behavior information includes at least one of a hand swing amplitude corresponding to different time periods, a foot swing amplitude corresponding to different time periods, a second upper scale locking duration, or a second measurement duration, where the second upper scale locking duration is an upper scale locking duration of a user stored by the electronic device, and the second measurement duration is a measurement duration of the user stored by the electronic device.

In one possible implementation, the first sign data includes at least one of a first weight, a first heart rate, or a first body fat rate.

In one possible implementation, the second sign data includes at least one of a second weight, a second heart rate, or a second body fat rate, where the second weight is a weight of the user stored by the electronic device, the second heart rate is a heart rate measured by the electronic device on the user of the electronic device, and the second body fat rate is a body fat rate of the user stored by the electronic device.

In a possible implementation manner, the measurement information further includes first sign data obtained by the body fat scale measuring the measured user;

the electronic equipment obtains the measurement information of the tested user from the body fat scale, and the method comprises the following steps:

the electronic equipment receives an identification instruction broadcast by the body fat scale, wherein the identification instruction comprises the first behavior information;

the electronic equipment responds to the received identification instruction and sends at least one data request;

and the body fat scale responds to the received at least one data request and transmits the first sign data so that the electronic equipment receives the first sign data.

the electronic equipment receives an identification instruction broadcast by the body fat scale;

and the body fat scale responds to the received at least one data request and sends the first behavior information and the first feature data so that the electronic equipment receives the first behavior information and the first feature data.

In a possible implementation manner, the identification reference information further includes a measurement distance, where the measurement distance is a distance between the electronic device and the body fat scale; after receiving the identification instruction broadcast by the body fat scale, the electronic equipment further comprises:

and the electronic equipment calculates the measurement distance according to the RSSI indicated by the received signal strength of the identification instruction.

In a possible implementation manner, the identification reference information further includes a measurement distance, where the measurement distance is a distance between the electronic device and the body fat scale, and the electronic device includes a mobile phone, a smart bracelet, or a smart watch;

The method further comprises the steps of:

the electronic equipment detects whether the electronic equipment is held or worn by a user by judging whether the difference value between the height of the user of the electronic equipment and the measured distance is within a first distance range;

and if the electronic equipment judges that the difference value between the height of the user of the electronic equipment and the measured distance is within a first distance range, detecting that the electronic equipment is held or worn by the user, and executing the step that the electronic equipment acquires the measured information of the measured user from the body fat scale or executing the step that the electronic equipment generates a matching result according to the measured information and the identification reference information.

In one possible implementation, the electronic device is a smart bracelet or a smart watch;

the method further comprises the steps of:

the electronic equipment detects whether the electronic equipment is worn on the wrist or the foot of a user according to the wearing behavior of the user;

when the electronic equipment detects that the electronic equipment is worn on the wrist or the foot of a user, executing the step that the electronic equipment acquires the measurement information of the tested user from the body fat scale or executing the step that the electronic equipment generates a matching result according to the measurement information and the identification reference information.

In one possible implementation, the matching result is a confidence level.

A second aspect provides a user identification method, the method being applied to an electronic device, the electronic device and a body fat scale communicating based on a short-range wireless communication protocol;

the method comprises the following steps:

the electronic equipment acquires measurement information of a measured user from the body fat scale, wherein the measurement information of the measured user comprises first behavior information, and the first behavior information is used for representing the measurement behavior of the measured user, which is detected when the body fat scale measures the physical sign data of the measured user;

the electronic equipment generates a matching result according to the measurement information and the identification reference information, wherein the matching result is used for representing the probability that a user of the electronic equipment is the tested user so as to enable the body fat scale to acquire the matching result, and whether the user of the electronic equipment is the tested user is judged according to the matching result of the at least one electronic equipment.

A third aspect provides a user identification method applied to a body fat scale, the body fat scale in communication with the at least one electronic device based on a short-range wireless communication protocol;

the method comprises the following steps:

the body fat scale obtains a matching result generated according to the measurement information and identification reference information of a user of the electronic equipment from the at least one electronic equipment, wherein the matching result is used for representing the probability that the user of the electronic equipment is the tested user, the identification reference information comprises second behavior information, and the second behavior information is used for representing the behavior of the user of the electronic equipment;

before the body fat scale obtains a matching result generated according to the measurement information and the identification reference information of the user of the electronic device from the at least one electronic device, the body fat scale further comprises:

the body fat scale broadcasts an identification instruction, wherein the identification instruction comprises the first behavior information, so that the electronic equipment responds to the received identification instruction and sends at least one data request;

The body fat scale broadcasts an identification instruction, so that the electronic equipment responds to the received identification instruction and sends at least one data request;

A fourth aspect provides an electronic device comprising: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the electronic device, cause the electronic device to perform the second aspect or any of the possible implementations of the second aspect of the user identification method.

A fifth aspect provides a body fat scale comprising: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the body fat scale, cause the body fat scale to perform the third aspect or any possible implementation of the third aspect of the user identification method.

A sixth aspect provides a computer readable storage medium comprising a stored program, wherein the program when run controls a device in which the computer readable storage medium is located to perform the user identification method of the second aspect or any possible implementation of the third aspect.

A seventh aspect provides a computer program product comprising instructions which, when run on a computer or any of the at least one processors, cause the computer to perform the or perform the method of user identification of the or any of the possible implementations of the second aspect.

In the technical scheme provided by the embodiment of the invention, the body fat scale acquires the measurement information of the measured user, wherein the measurement information of the measured user comprises first behavior information or comprises first behavior information and first sign data; the electronic equipment acquires identification reference information of a user of the electronic equipment, wherein the identification reference information comprises second behavior information or comprises the second behavior information and second sign data; the electronic equipment acquires measurement information of a user to be measured from the body fat scale; the electronic equipment generates a matching result according to the measurement information and the reference identification information; the body fat scale obtains a matching result from at least one electronic device; and judging whether the user of the electronic equipment is a tested user or not according to the matching result of at least one electronic equipment by the body fat scale. According to the embodiment of the invention, the user to be tested is identified through the reference identification information acquired by the electronic equipment and the measurement information acquired by the body fat scale, so that the accuracy of user identification is improved.

[ description of the drawings ]

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of a related art user identification method;

FIG. 2 is a schematic diagram of another related art user identification system;

FIG. 3a is a schematic diagram of a user identification system in some embodiments;

FIG. 3b is a schematic diagram of another user identification system in some embodiments;

FIG. 4 is a schematic diagram of the hardware architecture of an electronic device of some embodiments;

FIG. 5 is a flow chart of a user identification method in some embodiments;

FIG. 6 is a flow chart of a user identification method in other embodiments;

FIG. 7 is a flow chart of a user identification method in other embodiments;

FIG. 8 is a flow chart of a user identification method in other embodiments.

[ detailed description ] of the invention

For a better understanding of the technical solution of the present invention, the following detailed description of the embodiments of the present invention refers to the accompanying drawings.

It should be understood that the described embodiments are merely some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be understood that the term "and/or" as used herein is merely one way of describing an association of associated objects, meaning that there may be three relationships, e.g., a and/or b, which may represent: the first and second cases exist separately, and the first and second cases exist separately. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.

Body Fat scales (Body Fat scales) may measure sign data that may include, in addition to Body weight, multiple item component data including, for example, but not limited to, body Fat rate, skeletal muscle mass, protein rate, water rate, and the like. Intelligent wireless fidelity (wireless fidelity, wi-Fi) body fat scales are increasingly used as a family-shared body fat scale. Compared with the traditional body fat scale, the Wi-Fi body fat scale can intelligently identify a user, and after the user performs weighing measurement, the body fat scale can automatically send sign data to an account number of the identified user.

In the related art, the body fat scale can perform user identification through the body weight or body fat rate and other body data of the current user, but the accuracy of user identification is low. In the case that the body fat scale measures the weight of the current user after the current user scales, if the difference between the weight of the current user and the weight of the other user already bound with the body fat scale is smaller than or equal to a set weight threshold, the body fat scale indicates that the weight of the current user is close to the weight of the other user, and the body fat scale mistakenly recognizes the current user as the other user due to the collision of weight data, so that the accuracy of user recognition is reduced. Fig. 1 is a schematic diagram of a user identification method in the related art, as shown in fig. 1, in another case, the current user is a new user who is not bound to the body fat scale, after the current user gets on the scale, the body fat scale measures the weight of the current user, if the difference between the weight of the current user and the weight of the user who is bound to the body fat scale is greater than a set weight threshold, which indicates that the weight of the current user differs greatly from the weight of the user who is bound to the body fat scale, the body fat scale cannot identify the current user, and then the body fat scale sends the weight of the unidentified current user to a cloud server, and the cloud server pushes a message including the weight of the current user to all the mobile phones of the users in the user list, for example, as shown in fig. 1, the cloud server pushes a message including the weight of the current user to the mobile phones of the user a and the mobile phones of the user B, and the user actively recognizes the weight of the current user on the mobile phones, so that the experience of the user is not good, and the body fat scale cannot identify the user alone according to the weight of the user, so that the user identification accuracy is also low.

In another related art, a camera is added to a body fat scale to perform face recognition so as to identify a user through a face recognition technology. Fig. 2 is a schematic structural diagram of another related art user identification system, as shown in fig. 2, where the user identification system includes a body fat scale, a user terminal and a cloud device, the body fat scale includes a body fat scale assembly and a power module, the body fat scale assembly includes a face recognition module, a display module, a weight and electrical impedance acquisition module and a data transmission module, and the face recognition module may include a camera. The data transmission module is connected with the face recognition module, the display module, the weight and electrical impedance acquisition module and the cloud server, the display module is connected with the weight and electrical impedance acquisition module, the user terminal is connected with the body fat scale assembly, and the power module is connected with the body fat scale assembly. The power module is used for supplying power to the body fat scale assembly, the face recognition module is used for recognizing face of a user on the scale to obtain a user recognition result, and the weight and electrical impedance acquisition module is used for acquiring original sign data of the user and sending the original sign data to the display module, wherein the original sign data comprise weight, human body impedance and the like. The display module is used for calculating target sign data according to the collected original sign data and displaying the target sign data, wherein the target sign data comprises body fat rate, water rate and the like. The body weight and electrical impedance acquisition module is further used for sending original sign data to the cloud server through the data transmission module, the display module is further used for sending calculated target sign data to the cloud server through the data transmission module, the face recognition module is further used for sending a user recognition result to the cloud server through the data transmission module, and the user recognition result is used for recognizing a current user. And the cloud server sends the original sign data, the target sign data and the user identification result to the user terminal. In another related art shown in fig. 2, a camera is added to a body fat scale to perform face recognition to obtain a user recognition result, so that a current user is recognized through the user recognition result, and thus the accuracy of user recognition is improved. However, the proposal needs to add a camera on the body fat scale, thereby increasing the cost of the product; meanwhile, in order to perform face recognition, face information needs to be stored in the body fat scale, which can involve the problem of privacy protection, so that the risk of disclosure of private data of a user is increased. In addition, in the related art, the user can be identified by the foot print identification technology, and the product cost is increased by the scheme.

In summary, in the related art, in order to reduce the cost of the product, the current body fat scale mainly performs user identification based on the sign data of the user, for example, the sign data may include body weight or body fat rate. But the user cannot be accurately identified by using the body weight or body fat rate and other data, so that the accuracy of user identification is low.

In order to solve the technical problems, the embodiment of the invention provides a user identification system. Fig. 3a is a schematic structural diagram of a user identification system in some embodiments, and fig. 3b is a schematic structural diagram of another user identification system in some embodiments, where the user identification system may include a body fat scale 200 and at least one electronic device 100, and the body fat scale 200 and the at least one electronic device 100 communicate via a short-range wireless communication protocol, as shown in fig. 3a and 3 b.

In the embodiment of the invention, the short-distance wireless communication protocol can be Bluetooth and/or Wi-Fi.

As shown in fig. 3b, the body fat scale 200 may include a bluetooth module, for example, the bluetooth module may be a bluetooth low energy (bluetooth low energy, BLE) module, and the body fat scale 200 may perform bluetooth communication with the at least one electronic device 100 through the BLE module. The body fat scale 200 may further include a Wi-Fi module, the body fat scale 200 may perform Wi-Fi communication with the at least one electronic device 100 through the Wi-Fi module, and the body fat scale 200 may upload the measured measurement information to the cloud server through the Wi-Fi module. The body fat scale 200 further comprises a behavior acquisition module and a sign acquisition module, wherein the behavior acquisition module is used for measuring first behavior information of a user to be measured, and the sign acquisition module is used for measuring sign data. The body fat scale 200 also includes a distributed cooperative primary module. The body fat scale 200 also includes a System On Chip (SOC).

With the advent of the worldwide interconnecting age, users often have multiple electronic devices 100, and in some embodiments, electronic devices 100 include, but are not limited to, piggybacking

Or other operating system devices, including but not limited to cell phones, wearable devices, etc., which may be smart watches or smart bracelets. The user can wear the intelligent watch on the wrist; the user may wear the smart band on the wrist or on the foot. Wherein, for the case that the user wears the smart bracelet on the foot, for example, the user can pass the smart bracelet throughThe shoe buckle is tied on the shoelace of the shoe.

Any suitable standard, such as a distributed linkage protocol, may be complied with between the body fat scale 200 and the electronic device 100.

As shown in fig. 3b, the electronic device 100 may comprise a bluetooth module, which may be, for example, a BLE module. The electronic device 100 may communicate with the body fat scale 200 via a BLE module. The electronic device 100 further includes a Wi-Fi module through which the electronic device 100 may communicate with the body fat scale 200. The electronic device 100 also includes a distributed collaboration sub-module. The distributed cooperative submodules of the electronic device 100 implement distributed linkage with the distributed cooperative main module of the body fat scale 200 to implement user identification, for example, steps 108 to 114 in fig. 5, steps 208 to 218 in fig. 6, steps 308 to 318 in fig. 7, and steps 408 to 418 in fig. 8.

As shown in fig. 4, a schematic hardware structure of the electronic device in fig. 3a or fig. 3B is provided, and as shown in fig. 4, the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (universal serial bus, USB) interface 130, a charge management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a key 190, a motor 191, an indicator 192, a camera 193, a display 194, a subscriber identity module (subscriber identification module, SIM) card interface 195, and the like. It should be understood that the illustrated structure of the embodiment of the present invention does not constitute a specific limitation on the electronic device 100. In other embodiments of the invention, electronic device 100 may include more or fewer components than shown, or certain components may be combined, or certain components may be split, or different arrangements of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The processor 110 may include one or more processing units, such as: the processor 110 may include an application processor (application processor, AP), a modem processor, a graphics processor (graphics processing unit, GPU), an image signal processor (image signal processor, ISP), a controller, a video codec, a digital signal processor (digital signal processor, DSP), a baseband processor, and/or a neural network processor (neural-network processing unit, NPU), etc. Wherein the different processing units may be separate devices or may be integrated in one or more processors. The controller can generate operation control signals according to the instruction operation codes and the time sequence signals to finish the control of instruction fetching and instruction execution. A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may hold instructions or data that the processor 110 has just used or recycled. If the processor 110 needs to reuse the instruction or data, it can be called directly from the memory. Repeated accesses are avoided and the latency of the processor 110 is reduced, thereby improving the efficiency of the system.

In some embodiments, the processor 110 may include one or more interfaces. The interfaces may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous receiver transmitter (universal asynchronous receiver/transmitter, UART) interface, a mobile industry processor interface (mobile industry processor interface, MIPI), a general-purpose input/output (GPIO) interface, a subscriber identity module (subscriber identity module, SIM) interface, and/or a universal serial bus (universal serial bus, USB) interface, among others. It should be understood that the interfacing relationship between the modules illustrated in the embodiments of the present invention is only illustrative, and is not meant to limit the structure of the electronic device 100. In other embodiments of the present invention, the electronic device 100 may also employ different interfacing manners in the above embodiments, or a combination of multiple interfacing manners.

The charge management module 140 is configured to receive a charge input from a charger. The charger can be a wireless charger or a wired charger. In some wired charging embodiments, the charge management module 140 may receive a charging input of a wired charger through the USB interface 130. In some wireless charging embodiments, the charge management module 140 may receive wireless charging input through a wireless charging coil of the electronic device 100. The charging management module 140 may also supply power to the electronic device through the power management module 141 while charging the battery 142.

The power management module 141 is used for connecting the battery 142, and the charge management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charge management module 140 to power the processor 110, the internal memory 121, the display 194, the camera 193, the wireless communication module 160, and the like. The power management module 141 may also be configured to monitor battery capacity, battery cycle number, battery health (leakage, impedance) and other parameters. In other embodiments, the power management module 141 may also be provided in the processor 110. In other embodiments, the power management module 141 and the charge management module 140 may be disposed in the same device.

The wireless communication function of the electronic device 100 may be implemented by the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, a modem processor, a baseband processor, and the like. The antennas 1 and 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the electronic device 100 may be used to cover a single or multiple communication bands. Different antennas may also be multiplexed to improve the utilization of the antennas. For example: the antenna 1 may be multiplexed into a diversity antenna of a wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 150 may provide a solution for wireless communication including 2G/3G/4G/5G/6G, etc. applied on the electronic device 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (low noise amplifier, LNA), etc. The mobile communication module 150 may receive electromagnetic waves from the antenna 1, perform processes such as filtering, amplifying, and the like on the received electromagnetic waves, and transmit the processed electromagnetic waves to the modem processor for demodulation. The mobile communication module 150 can amplify the signal modulated by the modem processor, and convert the signal into electromagnetic waves through the antenna 1 to radiate. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be disposed in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 may be provided in the same device as at least some of the modules of the processor 110. The modem processor may include a modulator and a demodulator. The modulator is used for modulating the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used for demodulating the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low frequency baseband signal to the baseband processor for processing. The low frequency baseband signal is processed by the baseband processor and then transferred to the application processor. The application processor outputs sound signals through an audio device (not limited to the speaker 170A, the receiver 170B, etc.), or displays images or video through the display screen 194. In some embodiments, the modem processor may be a stand-alone device. In other embodiments, the modem processor may be provided in the same device as the mobile communication module 150 or other functional module, independent of the processor 110.

The wireless communication module 160 may provide solutions for wireless communication including wireless local area network (wireless local area networks, WLAN) (e.g., wireless fidelity (wireless fidelity, wi-Fi) network), bluetooth (BT), global navigation satellite system (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), near field communication technology (near field communication, NFC), infrared technology (IR), etc., as applied on the electronic device 100. The wireless communication module 160 may be one or more devices that integrate at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, modulates the electromagnetic wave signals, filters the electromagnetic wave signals, and transmits the processed signals to the processor 110. The wireless communication module 160 may also receive a signal to be transmitted from the processor 110, frequency modulate it, amplify it, and convert it to electromagnetic waves for radiation via the antenna 2.

In some embodiments, antenna 1 and mobile communication module 150 of electronic device 100 are coupled, and antenna 2 and wireless communication module 160 are coupled, such that electronic device 100 may communicate with a network and other devices through wireless communication techniques. The wireless communication techniques may include the Global System for Mobile communications (global system for mobile communications, GSM), general packet radio service (general packet radio service, GPRS), code division multiple access (code division multiple access, CDMA), wideband code division multiple access (wideband code division multiple access, WCDMA), time division code division multiple access (time-division code division multiple access, TD-SCDMA), long term evolution (long term evolution, LTE), 5G and subsequent evolution standards, BT, GNSS, WLAN, NFC, FM, and/or IR techniques, among others. The GNSS may include a global satellite positioning system (global positioning system, GPS), a global navigation satellite system (global navigation satellite system, GLONASS), a beidou satellite navigation system (beidou navigation satellite system, BDS), a quasi zenith satellite system (quasi-zenith satellite system, QZSS) and/or a satellite based augmentation system (satellite based augmentation systems, SBAS).

The electronic device 100 implements display functions through a GPU, a display screen 194, an application processor, and the like. The GPU is a microprocessor for image processing, and is connected to the display 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute instructions to generate or change display information. Electronic device 100 may implement shooting functionality through an ISP, one or more cameras 193, video codecs, a GPU, one or more display screens 194, an application processor, and the like.

The external memory interface 120 may be used to connect an external memory card, such as a Micro SD card, to enable expansion of the memory capabilities of the electronic device 100. The external memory card communicates with the processor 110 through an external memory interface 120 to implement data storage functions. For example, files such as music, video, etc. are stored in an external memory card.

The internal memory 121 may be used to store computer executable program code including instructions. The internal memory 121 may include a storage program area and a storage data area. The storage program area may store an application program (such as a sound playing function, an image playing function, etc.) required for at least one function of the operating system, etc. The storage data area may store data created during use of the electronic device 100 (e.g., audio data, phonebook, etc.), and so on. In addition, the internal memory 121 may include a high-speed random access memory, and may further include a nonvolatile memory such as at least one magnetic disk storage device, a flash memory device, a universal flash memory (universal flash storage, UFS), and the like. The processor 110 performs various functional applications of the electronic device 100 and data processing by executing instructions stored in the internal memory 121 and/or instructions stored in a memory provided in the processor.

The electronic device 100 may implement audio functions through an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, an application processor, and the like. Such as music playing, recording, etc.

The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, and the like. The touch sensor 180K is also referred to as a "touch device". The touch sensor 180K may be disposed on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, which is also called a "touch screen". The touch sensor 180K is for detecting a touch operation acting thereon or thereabout. The touch sensor may communicate the detected touch operation to the application processor to determine the touch event type. Visual output related to touch operations may be provided through the display 194. In other embodiments, the touch sensor 180K may also be disposed on the surface of the electronic device 100 at a different location than the display 194.

The SIM card interface 195 is used to connect a SIM card. The SIM card may be inserted into the SIM card interface 195, or removed from the SIM card interface 195 to enable contact and separation with the electronic device 100. The electronic device 100 may support 1 or N SIM card interfaces, N being a positive integer greater than 1. The SIM card interface 195 may support Nano SIM cards, micro SIM cards, and the like. The same SIM card interface 195 may be used to insert multiple cards simultaneously. The types of the plurality of cards may be the same or different. The SIM card interface 195 may also be compatible with different types of SIM cards. The SIM card interface 195 may also be compatible with external memory cards. The electronic device 100 interacts with the network through the SIM card to realize functions such as communication and data communication. In some embodiments, the electronic device 100 employs esims, i.e.: an embedded SIM card. The eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100.

In order to solve the problem of low accuracy of user identification in the related art, the embodiment of the invention provides a user identification method which is realized based on a body fat scale and at least one electronic device. The body fat scale acquires measurement information of a measured user, wherein the measurement information of the measured user comprises first behavior information or comprises first behavior information and first sign data; the electronic equipment acquires identification reference information of a user of the electronic equipment, wherein the identification reference information comprises second behavior information or comprises the second behavior information and second sign data; the electronic equipment acquires measurement information of a user to be measured from the body fat scale; the electronic equipment generates a matching result according to the measurement information and the reference identification information; the body fat scale obtains a matching result from at least one electronic device; and judging whether the user of the electronic equipment is a tested user or not according to the matching result of at least one electronic equipment by the body fat scale. According to the embodiment of the invention, the user to be tested is identified through the reference identification information acquired by the electronic equipment and the measurement information acquired by the body fat scale, so that the accuracy of user identification is improved.

As shown in fig. 3a, the user to be measured is a user standing on the body fat scale 200 to perform measurement, namely: the user to be tested is the user who gets on the scale.

The user of the electronic device 100 is a hand-held electronic device 100 or a user wearing the electronic device 100. For example, as shown in fig. 3a, if the electronic device 100 is a mobile phone, the user C is a user holding the mobile phone; if the electronic device 100 is a smart watch, the user D is a user wearing the smart watch on the wrist; if the electronic device 100 is a smart bracelet, the user E is a user wearing the smart bracelet on the wrist, or the user E is a user wearing the smart bracelet on the foot. One body fat scale 200 may communicate with a plurality of users 'electronic devices 100 based on a short-range wireless communication protocol, namely user C's electronic device 100, user D's electronic device 100, and user E's electronic device 100. The user under test and the user of the electronic device 100 may be the same user, or the user under test and the user of the electronic device 100 may be different users.

As shown in fig. 3a, the body fat scale 200 acquires measurement information of a user under test. The body fat scale 200 is arranged on the tested user station to measure, and the body fat scale 200 measures the tested user to obtain the measurement information of the tested user. The process by which the body fat scale 200 measures a measured user may include four actions, which may include a scale up action, a scale up lock action, a measure action, and a scale down action. The hand of the user to be measured can swing at a certain angle in the process of weighing up and weighing down, and can swing at the same time; the foot of the user to be measured can swing at a certain angle in the process of the weighing action and the weighing action, and the foot of the user to be measured can swing at the foot of the user to be measured. The measured information of the measured user may include the first behavior information or include the first behavior information and first characteristic data obtained by measuring the measured user by the body fat scale 200. The first behavior information is used to characterize the measured behavior of the measured user detected when the body fat scale 200 measures the vital sign data of the measured user, for example, the first behavior information includes at least one of a scale up period, a first scale up lock period, a first measurement period, or a scale down period. The time period of weighing is the time period from the time point of weighing on the first foot to the time point of weighing on the second foot of the user to be tested; the time length of the scale loading locking is the time length from standing to weight locking after the user to be measured loads the scale, for example, the range of the scale loading locking time length is 2 seconds to 3 seconds; the measured time length is the time length of the measured physical sign data of the user after the weight is locked; the lower scale time period is the time period between the time point of the first foot lower scale of the tested user and the time point of the second foot lower scale. The first sign data includes at least one of a first weight, a first heart rate, or a first body fat rate.

As shown in fig. 3a, the electronic device 100 obtains identification reference information of a user of the electronic device, the identification reference information comprising second behavior information or comprising second behavior information and second sign data, the second behavior information being used for characterizing a behavior of the user of the electronic device. For example, the second behavior information includes at least one of a hand swing amplitude corresponding to a different time period, a foot swing amplitude corresponding to a different time period, a second scale-up lock-up period, or a second measurement period, and the second characteristic data includes at least one of a second weight, a second heart rate, or a second body fat rate. The user of the electronic device is provided with a user identifier, for example, the user identifier is a user account, the user account of the electronic device can be associated with behavior information and physical sign data of the user, for example, the user account of the electronic device is associated with at least one of a second weighing scale locking duration, a second measurement duration, a second weight or a second body fat rate of the user, and the electronic device can pre-store at least one of the second weighing scale locking duration, the second measurement duration, the second weight or the second body fat rate. When a user of the electronic device performs measurement by using the body fat scale (the body fat scale used each time may be the same body fat scale or different body fat scales as the body fat scale 200 in fig. 3 a), the body fat scale may acquire behavior information and sign data of the user of the electronic device, the behavior information and sign data of the user acquired by the body fat scale are associated with a user account of the user, the electronic device may acquire an upper scale time period, a first upper scale locking time period, a first measurement time period, a lower scale time period, a first weight, a first heart rate and a first body fat rate corresponding to the user account of the user from the body fat scale, and specifically, the electronic device may acquire the behavior information and sign data of the user from the body fat scale through a short-range wireless communication protocol, for example, the short-range wireless communication protocol may be bluetooth or Wi-Fi. Furthermore, the electronic device may store a scale up time period, a first scale up lock time period, a first measurement time period, a scale down time period, a first weight, a first heart rate, and a first body fat rate corresponding to the user account of the user. For example, the second scale locking duration may be a scale locking duration of the user stored by the electronic device, where the scale locking duration of the user stored by the electronic device may be a first scale locking duration when the user last measured or may be an average of first scale locking durations when the user last measured several times; the second measurement duration may be a measurement duration of the user stored in the electronic device, where the measurement duration of the user stored in the electronic device may be a first measurement duration of the user when the user last measured or may be an average value of the first measurement durations of the user when the user last measured several times; the second weight is the weight of the user stored by the electronic device, wherein the weight of the user stored by the electronic device can be the first weight of the user when the user performs the measurement last time or can be the average value of the first weight when the user performs the measurement for the previous times; the second body fat rate is a body fat rate of the user stored by the electronic device, wherein the body fat rate of the user stored by the electronic device may be the first body fat rate when the user last measured or may be an average of the first body fat rates when the user last measured several times. In other words, the second upper scale locking time period is a historical upper scale locking time period of the user stored in the electronic device, the second measurement time period is a historical upper scale measurement time period of the user stored in the electronic device, the second body weight is a historical body weight of the user stored in the electronic device, and the second body fat rate is a historical body fat rate of the user stored in the electronic device. In the process that the electronic equipment acquires the identification reference information of the electronic equipment, the electronic equipment can measure the user of the electronic equipment to obtain a second heart rate, and the second heart rate is the heart rate obtained by the electronic equipment to measure the user of the electronic equipment.

When the user holds or wears the electronic device 100 on his wrist, the electronic device 100 may acquire the second behavior information in real time, for example, when the user swings his arm, the electronic device 100 held or worn by the user may detect that the user swings his arm and detects the swing amplitude of his hand and the time period of the swing of his hand, so the second behavior information acquired by the electronic device 100 may include the detected swing amplitudes of his hand corresponding to different time periods; or, when the electronic device 100 is worn on the foot of the user, the electronic device 100 detects the swing of the foot of the user and detects the swing amplitude of the foot and the time period of the swing of the foot, so the second behavior information obtained by the electronic device 100 may include the swing amplitude of the foot corresponding to the detected different time periods.

As shown in fig. 3a, the electronic device 100 may obtain measurement information of a user under test from the body fat scale 200. In the embodiment of the present invention, description will be given taking an example that measurement information of a user to be measured includes first behavior information and first sign data. As shown in fig. 3a, the body fat scale 200 broadcasts an identification instruction, for example, the body fat scale 200 broadcasts an identification instruction through a bluetooth communication technology or a Wi-Fi communication technology, the identification instruction being used to instruct the electronic device 100 that receives the identification instruction to cooperatively perform user identification. At least one electronic device 100 may receive the broadcasted identification instruction via bluetooth communication technology or Wi-Fi communication technology. For example, as shown in fig. 3a, in three electronic devices 100, the mobile phone receives the broadcast identification instruction through the bluetooth communication technology or the Wi-Fi communication technology, the smart watch receives the broadcast identification instruction through the bluetooth communication technology or the Wi-Fi communication technology, and the smart bracelet receives the broadcast identification instruction through the bluetooth communication technology or the Wi-Fi communication technology. The electronic device 100 learns that it needs to cooperate with the body fat scale 200 according to the identification instruction to complete the user identification process.

In some embodiments, the identification instructions broadcast by body fat scale 200 include first behavior information such that electronic device 100 obtains the first behavior information via the identification instructions. The electronic device 100 then transmits at least one data request in response to the identification instruction. The body fat scale 200 transmits vital sign data of the user under test in response to the received at least one data request.

As an alternative, if the data size of the vital sign data is larger, the electronic device 100 may sequentially send a plurality of data requests and receive the vital sign data sent by the body fat scale 200 in response to each data request multiple times in order to ensure that the vital sign data can be more reliably acquired due to the bandwidth limitation of the bluetooth communication or the Wi-Fi communication. For example, when each type of vital sign data corresponds to one data request, the plurality of data requests includes a weight data request, a heart rate data request, and a body fat rate request, the electronic device 100 transmits the weight data request, the body fat scale 200 transmits a first weight in response to the received weight data request, and the electronic device 100 receives the first weight; then, the electronic device 100 sends a heart rate data request to the body fat scale 200, and the body fat scale 200 sends a first heart rate in response to the received heart rate data request, so that the electronic device 100 receives the first heart rate; further, the electronic device 100 transmits a body fat rate data request to the body fat scale 200, and the body fat scale 200 transmits a first body fat rate in response to the received body fat rate data request, so that the electronic device 100 receives the first body fat rate. For another example, all types of vital sign data correspond to one data request, the electronic device 100 sends one data request, the body fat scale 200 sends a first weight in response to the received data request to cause the electronic device 100 to receive the first weight, and the body fat scale 200 sends a first heart rate in response to the received data request to cause the electronic device 100 to receive the first heart rate; the body fat scale 200 transmits a first body fat rate in response to the received data request to cause the electronic device 100 to receive the first body fat rate.

Alternatively, if the data amount of the physical sign data is large and the communication bandwidth between the body fat scale 200 and the electronic device 100 is also large, the electronic device 100 may send one data request, and the body fat scale 200 may send all the physical sign data at a time in response to the received data request so that the electronic device 100 receives all the physical sign data at a time. For example, the electronic device 100 may broadcast a data request, and the body fat scale 200 may send the first weight, the first heart rate, and the first body fat rate in response to the received data request such that the electronic device 100 receives the first weight, the first heart rate, and the first body fat rate at a time. Alternatively, if the amount of the physical sign data is small, the electronic device 100 may send a data request to the body fat scale 200, the body fat scale 200 may send the physical sign data in response to the data request so that the electronic device 100 receives the physical sign data, for example, the electronic device 100 may broadcast a data request, and the body fat scale 200 may send the first weight, the first heart rate, or the first body fat rate in response to the data request so that the electronic device 100 receives the first weight, the first heart rate, or the first body fat rate.

In other embodiments, the identification instructions broadcast by body fat scale 200 do not include first behavioral information. The electronic device 100 transmits at least one data request in response to the identification instruction; the body fat scale 200 transmits the first behavior information and the first characterization data in response to at least one data request such that the electronic device 100 receives the first behavior information and the first characterization data. As an alternative, to ensure that the first behavior information and the first characteristic data can be more reliably acquired due to the bandwidth limitation of the bluetooth communication or the Wi-Fi communication, the electronic device 100 may sequentially transmit a plurality of data requests and receive the first behavior information and the first characteristic data transmitted by the body fat scale 200 in response to each data request multiple times. For example, when the first behavioral information corresponds to one data request, each type of physical sign data corresponds to one data request, and the plurality of data requests includes a weight data request, a heart rate data request, and a body fat rate request, the electronic device 100 transmits the behavioral information data request, and the body fat scale 200 transmits the first behavioral information in response to the received behavioral information data request, so that the electronic device 100 receives the first behavioral information; the electronic device 100 sends a weight data request, the body fat scale 200 sends a first weight in response to the received weight data request, and the electronic device 100 receives the first weight; then, the electronic device 100 sends a heart rate data request to the body fat scale 200, and the body fat scale 200 sends a first heart rate in response to the received heart rate data request, so that the electronic device 100 receives the first heart rate; further, the electronic device 100 transmits a body fat rate data request to the body fat scale 200, and the body fat scale 200 transmits a first body fat rate in response to the received body fat rate data request, so that the electronic device 100 receives the first body fat rate. As another alternative, the electronic device 100 may also send a data request to obtain the first behavior information and the first feature data at a time, which will not be described in detail.

As shown in fig. 3a, the identification reference information acquired by the electronic device 100 may include a measurement distance, where the measurement distance is a distance between the electronic device 100 and the body fat scale 200. The electronic device 100 calculates the measurement distance according to the received signal strength indication (received signal strength indication, RSSI) of the identification instruction after receiving the identification instruction broadcast by the body fat scale 200. Specifically, the electronic device 100 may pass through the formula: d=10 ((abs (RSSI) -a)/(10×n)), where d is the measurement distance, RSSI is the received signal strength indication, a is the signal strength when the body fat scale 200 and the electronic device 100 are separated by 1 meter, and n is the environmental attenuation factor.

If the electronic device 100 is a mobile phone, the electronic device 100 detects whether the electronic device 100 is held by the user C by determining whether the difference between the height of the user C of the electronic device 100 and the measured distance is within a first distance range; when the electronic device 100 determines that the difference between the height and the measured distance of the user C is within the first distance range, it detects that the electronic device 100 is held by the user C, and performs a step in which the electronic device 100 obtains the measured information of the measured user from the body fat scale or performs a step in which the electronic device 100 generates a matching result according to the measured information and the identification reference information.

If the electronic device 100 is an intelligent bracelet or an intelligent watch, the electronic device 100 detects whether the electronic device 100 is held by the user D by judging whether the difference between the height and the measured distance of the user D of the electronic device 100 is within a first distance range; when the electronic device 100 determines that the difference between the height and the measured distance of the user D is within the first distance range, it detects that the electronic device 100 is held by the user D, and performs a step in which the electronic device 100 obtains the measured information of the measured user from the body fat scale or performs a step in which the electronic device 100 generates a matching result according to the measured information and the identification reference information.

If the electronic device 100 is a smart bracelet or a smart watch, the electronic device 100 detects whether the electronic device is worn on the wrist or the foot of the user according to the wearing behavior of the user. If the electronic device 100 detects that the electronic device is worn on the wrist or the foot of the user, the electronic device performs the step of acquiring the measurement information of the user to be measured from the body fat scale or the step of generating a matching result by the electronic device according to the measurement information and the reference identification information.

As shown in fig. 3a, the electronic device 100 generates a matching result according to the measurement information and the identification reference information, and the matching result is used for characterizing the probability that the user of the electronic device 100 is the tested user. As an alternative, the matching result may include a confidence, where the confidence may be used to characterize the probability that the user of the electronic device is the tested user, the greater the confidence the greater the probability that the user of the electronic device is the tested user.

As an alternative, when the electronic device 100 includes a mobile phone, a smart wristband worn on a wrist, or a smart watch, the measured information of the measured user includes first behavior information or includes first behavior information and first feature data, for example, the first behavior information includes at least one of a scales up period, a scales up locking period, a first measurement period, or a scales down period, and the first feature data may include at least one of a first body weight, a first heart rate, or a first body fat rate; the reference identification information may include second behavior information or may include second behavior information including, for example, at least one of a hand swing amplitude, a second upper scale locking period, or a second measurement period corresponding to different time periods, and second sign data including at least one of a second body weight, a second heart rate, or a second body fat rate.

As another alternative, when the electronic device 100 is a smart bracelet worn on the foot, the measured information of the measured user includes first behavior information or includes first behavior information and first feature data, for example, the first behavior information includes at least one of a time period for loading, a first time period for measuring, or a time period for unloading, and the first feature data may include at least one of a first weight, a first heart rate, or a first body fat rate; the reference identification information may include second behavior information or may include a second behavior information system and second characterization data, for example, the second behavior information may include at least one of a foot swing amplitude, a second upper scale locking period, or a second measurement period corresponding to different time periods, and the second characterization data may include at least one of a second weight, a second heart rate, or a second body fat rate.

As shown in fig. 3a, the body fat scale 200 obtains a matching result from at least one electronic device 100. For example, the electronic device 100 transmits a matching result, and the body fat scale 200 receives the matching result. As an alternative, when sending the matching result, the electronic device 100 further sends a user identifier corresponding to the matching result, where the user identifier is used to identify a user of the electronic device 100, and in some embodiments, the user identifier is an account of the user, for example, is a Hua account. For example, the mobile phone sends the confidence level and the user identification of the corresponding user C so that the body fat scale 200 receives the confidence level and the user identification of the corresponding user C, the smart watch sends the confidence level and the user identification of the corresponding user D so that the body fat scale 200 receives the confidence level and the user identification of the corresponding user D, and the smart bracelet sends the confidence level and the user identification of the corresponding user E so that the body fat scale 200 receives the confidence level and the user identification of the corresponding user E.

As shown in fig. 3a, the body fat scale 200 determines whether the user of the electronic device 100 is a tested user according to the matching result of at least one electronic device 100. Specifically, describing an example in which the matching result includes a plurality of confidence degrees, when the number of confidence degrees is a plurality of confidence degrees, the body fat scale 200 may determine that a user of the electronic device corresponding to the confidence degree that is greater than the set threshold value and the maximum confidence degree is the tested user; or when the number of the confidence degrees is one, if the body fat scale 200 judges that the confidence degrees are larger than the set threshold, the user of the electronic device corresponding to the confidence degrees is judged as the tested user.

For example, the body fat scale 200 screens out the confidence level greater than the set threshold from the confidence levels of the at least one electronic device 100, determines the maximum confidence level from the confidence levels greater than the set threshold, and determines the user of the electronic device corresponding to the maximum confidence level as the user to be tested. The user corresponding to the user identifier corresponding to the maximum confidence level can be determined as the user of the electronic device corresponding to the maximum confidence level. For example, if the user of the smart watch is user D and the confidence level greater than the set threshold is the confidence level of the smart watch, the body fat scale 200 determines the user D of the smart watch as the user under test. Thus, user D (or referred to as the user under test) wears the smart watch standing body fat scale 200 to make measurements.

It should be noted that: if the confidence level of at least one electronic device 100 is less than or equal to the confidence level of the set threshold, the body fat scale 200 determines that all the users of the electronic devices 100 are not the tested users, that is, the body fat scale 200 cannot identify the tested users.

According to the embodiment of the invention, the tested user is identified through the reference identification information acquired by the electronic equipment and the measurement information of the tested user acquired by the body fat scale, so that the accuracy of user identification is improved.

The workflow of the user identification method is illustrated by a specific embodiment. FIG. 5 is a flow chart of a user identification method in some embodiments, as shown in FIG. 5, comprising:

step 102, the body fat scale acquires measurement information of a measured user, wherein the measurement information of the measured user comprises first behavior information and first sign data, and the first behavior information is used for representing measurement behaviors of the measured user detected when the body fat scale measures the sign data of the measured user.

The body fat scale measures the measured user to obtain the measurement information of the measured user, and specifically, the measured user stands on the body fat scale to enable the body fat scale to measure the measured user.

The first behavior information includes at least one of an up-scale time period, a first up-scale lock-out period, a first measurement period, or a down-scale time period.

Step 104, the electronic device obtains identification reference information of the user of the electronic device, wherein the identification reference information comprises second behavior information and second sign data, and the second behavior information is used for representing the behavior of the user of the electronic device.

The second behavior information comprises at least one of hand swing amplitude corresponding to different time periods, foot swing amplitude corresponding to different time periods, second upper scale locking duration or second measurement duration.

In this embodiment, the step 102 and the step 104 are two steps that can be performed independently, for example, the step 102 may be performed before the step 104, or the step 104 may be performed before the step 102, or the step 102 and the step 104 may be performed simultaneously.

Step 106, the electronic device receives an identification instruction broadcast by the body fat scale, wherein the identification instruction comprises first behavior information.

The body fat scale broadcasts the identification instructions via a wireless communication technology, which may include, for example, bluetooth communication technology or Wi-Fi communication technology.

Step 108, the electronic device broadcasts at least one data request in response to the received identification instruction, and the body fat scale broadcasts first sign data in response to the received at least one data request, so that the electronic device receives the first sign data.

The first sign data includes at least one of a first weight, a first heart rate, or a first body fat rate.

The electronic device may obtain the first sign data from the body fat scale according to a preset collaborative behavior mode. The collaborative behavior mode is used for indicating which physical sign data the electronic equipment needs to acquire from the body fat scale. Each type of vital sign data corresponds to a data request, for example, if the type of vital sign data to be requested is N, the number of data requests to be sent is N, the step 108 may include: the electronic equipment broadcasts a data request 1 and receives first sign data 1 broadcast by the body fat scale in response to the data request 1; the electronic equipment broadcasts a data request 2 and receives first sign data 2 broadcast by the body fat scale in response to the data request 2; the electronic device sequentially broadcasts data requests until the electronic device 100 broadcasts a data request N to the body fat scale and receives first characterization data N broadcast by the body fat scale in response to the data request N.

Step 110, the electronic device generates a matching result according to the measurement information and the identification reference information, and the matching result is used for representing the probability that the user of the electronic device is the tested user.

Step 112, the body fat scale obtains a matching result from at least one electronic device.

The electronic device broadcasts the matching result to cause the body fat scale to receive the matching result.

And 114, judging whether the user of the electronic equipment is a tested user or not by the body fat scale according to the matching result of at least one electronic equipment.

In the embodiment of the invention, when the number of the confidence degrees is a plurality of, the body fat scale can judge the user of the electronic equipment corresponding to the confidence degree which is larger than the set threshold value and the maximum confidence degree in the plurality of confidence degrees as the tested user; or when the number of the confidence degrees is one, if the body fat scale judges that the confidence degrees are larger than the set threshold value, judging the user of the electronic equipment corresponding to the confidence degrees as a tested user.

In the embodiment of the present invention, as another alternative, the body fat scale and the electronic device may further perform data transmission through a peer-to-peer communication manner, where the peer-to-peer communication manner may include bluetooth peer-to-peer communication or Wi-Fi peer-to-peer communication, for example.

In the embodiment of the invention, further, the body fat scale can upload the first sign data of the tested user and the user identification result of the tested user to the cloud server, wherein the user identification result of the tested user can be the user identification of the identified tested user. The electronic equipment can acquire first sign data of the tested user corresponding to the user identifier from the cloud server.

According to the embodiment of the invention, under the condition of not increasing the cost of the body fat scale, the body fat scale is linked with the electronic equipment in a distributed linkage mode so as to identify the tested user, so that the accuracy of user identification is greatly improved.

In the embodiment of the invention, after the user directly goes up the scale, the body fat scale can identify the user through linkage with the electronic equipment, the user does not need to confirm on the mobile phone to claim the measurement information, and the physical sign data of the tested user is automatically pushed to the identified user, so that all users are not influenced, and the user experience is improved.

In the embodiment of the invention, the body fat scale can identify the user through being linked with the electronic equipment capable of near field communication, and basically can identify the user without errors through being linked with the electronic equipment capable of near field communication.

In the following, a workflow of a user identification method is illustrated by another specific embodiment, for example, the present embodiment shows a scenario where a body fat scale cooperates with a mobile phone, in which a user to be tested holds the mobile phone, stands on the body fat scale to measure, and the body fat scale and the mobile phone are linked to implement identification of the user to be tested. FIG. 6 is a flowchart of a user identification method in other embodiments, as shown in FIG. 6, where the electronic device may be a mobile phone, the method includes:

Step 202, the body fat scale acquires measurement information of a measured user, wherein the measurement information of the measured user comprises first behavior information and first sign data, and the first behavior information is used for representing measurement behaviors of the measured user detected when the body fat scale measures the sign data of the measured user.

The body fat scale measures the measured user to obtain measurement information, and specifically, the measured user stands on the body fat scale so that the body fat scale measures the measured user.

Step 204, the electronic device obtains identification reference information of the user of the electronic device, where the identification reference information includes second behavior information and second sign data, and the second behavior information is used to characterize a behavior of the user of the electronic device.

In this embodiment, the step 202 and the step 204 are two steps that can be performed independently, for example, the step 202 may be performed before the step 204, or the step 204 may be performed before the step 202, or the step 202 and the step 204 may be performed simultaneously.

Step 206, the electronic device receives the identification instruction broadcast by the body fat scale.

Step 208, the electronic device calculates a measurement distance according to the RSSI of the identification instruction, wherein the measurement distance is the distance between the electronic device and the body fat scale.

The body fat scale calculates the measurement distance through the RSSI of the identification instruction broadcasted by Bluetooth.

In the embodiment of the present invention, as another alternative, the body fat scale may also broadcast a ranging signal, where the ranging signal is only used to measure the distance between the electronic device and the body fat scale, and after the electronic device receives the ranging signal, the measured distance may be calculated according to the RSSI of the ranging signal, where the situation diagram is not specifically shown.

Step 210, when the electronic device determines that the difference between the height of the user of the electronic device and the measured distance is within the first distance range, the electronic device is detected to be held by the user.

For example, if it is determined that the difference between the height of the user of the electronic device and the measured distance is within the first distance range, it indicates that the user holds the mobile phone. For example, the first distance range is less than 2 meters.

For example, if the electronic device determines that the difference between the height and the measured distance of the user of the electronic device is not within the first distance range, it indicates that the user does not hold the mobile phone, and the electronic device does not execute the following steps 212 to 216.

Step 212, the electronic device broadcasts a plurality of data requests in response to the identification instruction, and receives first behavior information and first characterization data broadcast by the body fat scale in response to the plurality of data requests.

The electronic device can acquire the first behavior information and the first sign data from the body fat scale according to a preset cooperative behavior mode. In this embodiment, the cooperative behavior pattern is used to indicate that the electronic device needs to acquire the first behavior information from the body fat scale and the first body weight in the first sign data, and the step 212 may include: the electronic equipment broadcasts a behavior information data request and receives first behavior information broadcast by the body fat scale in response to the behavior information data request; the electronic device broadcasts a weight data request and receives a first weight broadcast by the body fat scale in response to the weight data request.

Step 214, the electronic device generates a matching result according to the measurement information and the identification reference information, where the matching result is used to characterize the probability that the user of the electronic device is the tested user.

In the embodiment of the invention, the matching result comprises confidence. For example, the first behavior information includes an upper scale time period, a first upper scale locking time period, a first measurement time period and a lower scale time period, the first behavior information includes a first weight, the second behavior information includes hand swing amplitudes of different time periods, a second upper scale time period and a second measurement time period, the second behavior data includes a second weight, the electronic device matches the hand swing amplitudes of the upper scale time period and the different time periods to generate a sub-confidence corresponding to the hand swing amplitudes of the upper scale, the electronic device matches the hand swing amplitudes of the lower scale time period and the different time periods to generate a sub-confidence corresponding to the hand swing amplitudes of the lower scale, the electronic device matches the first upper scale locking time period and the second upper scale locking time period to generate a sub-confidence corresponding to the upper scale locking time period, the electronic device matches the first measurement time period and the second measurement time period to generate a sub-confidence corresponding to the measurement time period, and the electronic device matches the first weight and the second body weight to generate a sub-confidence corresponding to the weight. The electronic equipment performs weighted summation calculation or weighted average calculation on the sub-confidence coefficient corresponding to the hand swing amplitude of the upper scale, the sub-confidence coefficient corresponding to the hand swing amplitude of the lower scale, the sub-confidence coefficient corresponding to the locking time length of the upper scale, the sub-confidence coefficient corresponding to the measuring time length and the sub-confidence coefficient corresponding to the weight, and generates the confidence coefficient.

Table 1 shows the confidence levels corresponding to the different behavior pattern information.

TABLE 1

As shown in table 1 above, the behavior patterns include an upper scale behavior, an upper scale locking behavior, a measurement behavior and a lower scale behavior, wherein behavior pattern information corresponding to the upper scale behavior includes a hand swing amplitude of the upper scale and a foot swing amplitude of the upper scale, behavior pattern information corresponding to the upper scale locking behavior includes an upper scale locking duration, behavior pattern information corresponding to the measurement behavior includes a measurement duration, a body weight, a heart rate and a measurement distance, and behavior pattern information corresponding to the lower scale behavior includes a hand swing amplitude of the lower scale and a foot swing amplitude of the lower scale. Each behavior pattern information corresponds to three confidences, specifically, the three confidences corresponding to each behavior pattern information include a coincidence confidence, an uncertainty confidence, and an unconformity confidence. Wherein the confidence, uncertainty confidence, and uncertainty confidence may be set according to experimental data. For example, the confidence in the confidence may be greater than the uncertainty confidence, the uncertainty confidence may be greater than the uncertainty confidence, and then the probability that the user of the electronic device characterized by the confidence is the measured user is greater than the probability that the user of the electronic device characterized by the uncertainty confidence is the measured user, and the probability that the user of the electronic device characterized by the uncertainty is the measured user is greater than the probability that the user of the electronic device characterized by the uncertainty is the measured user.

The electronic equipment matches the hand swing amplitude of the upper scale time period and different time periods to generate the sub-confidence coefficient corresponding to the hand swing amplitude of the upper scale. The electronic equipment judges whether the hand swing amplitude exists in the upper scale time period according to the hand swing amplitude of different time periods, and if the hand swing amplitude exists in the upper scale time period, the electronic equipment determines that the sub-confidence coefficient corresponding to the hand swing amplitude of the upper scale is the first sub-confidence coefficient, wherein the hand swing amplitude indicates that the corresponding hand swing amplitude can be matched in the upper scale time period. If the electronic equipment judges that the hand swing amplitude does not exist in the upper scale time period, and the electronic equipment indicates that the upper scale time period cannot be matched with the corresponding hand swing amplitude, the sub-confidence degree corresponding to the hand swing amplitude of the upper scale is determined to be the second sub-confidence degree. As shown in table 1 above, for example, if the first sub-confidence is the confidence, the sub-confidence corresponding to the hand swing amplitude of the upper scale is 0.2. For example, if the second sub-confidence includes a non-conforming confidence or an uncertain confidence, the electronic device may further identify the second sub-confidence. When the electronic device acquires the reference identification information, if the hand of the user of the electronic device is in a static state, the second behavior information acquired by the electronic device can further comprise hand static state information in different time periods, the hand static state information is used for representing that the hand of the user is in a static state, the hand of the user does not swing, at the moment, if the electronic device judges that the hand swing amplitude does not exist in the upper scale time period, the electronic device can also match the hand static state information in the upper scale time period with the hand static state information in different time periods to generate a sub-confidence corresponding to the hand swing amplitude of the upper scale, specifically, the electronic device judges whether the hand static state information exists in the upper scale time period according to the hand static state information in different time periods, if the hand static state information exists in the upper scale time period, the hand of the user is indicated to be in the static state without the hand swing action, the second sub-confidence is determined to be in a non-confidence, and the sub-confidence corresponding to the hand swing amplitude of the upper scale is 0; if it is judged that the hand rest state information does not exist in the upper scale time period, and because the hand swing amplitude does not exist in the upper scale time period under the condition, the electronic equipment cannot determine whether the hand of the user is in the rest state or the hand swing state in the upper scale time period, the second sub-confidence degree is determined to be the uncertain confidence degree, and the sub-confidence degree corresponding to the hand swing amplitude of the upper scale is 0.

The electronic equipment matches the hand swing amplitude of the lower scale time period and different time periods to generate the sub-confidence coefficient corresponding to the hand swing amplitude of the lower scale. The electronic equipment judges whether the hand swing amplitude exists in the lower scale time period according to the hand swing amplitude of different time periods, and if the hand swing amplitude exists in the lower scale time period, the electronic equipment determines that the sub-confidence coefficient corresponding to the hand swing amplitude of the lower scale is the first sub-confidence coefficient, wherein the hand swing amplitude indicates that the lower scale time period can be matched with the corresponding hand swing amplitude. If the electronic equipment judges that the hand swing amplitude does not exist in the lower scale time period, and the electronic equipment indicates that the lower scale time period cannot be matched with the corresponding hand swing amplitude, the sub-confidence degree corresponding to the hand swing amplitude of the lower scale is determined to be the second sub-confidence degree. As shown in table 1 above, for example, if the first sub-confidence is the confidence, the sub-confidence corresponding to the hand swing amplitude of the lower scale is 0.6. For example, if the second sub-confidence includes a non-conforming confidence or an uncertain confidence, the electronic device may further identify the second sub-confidence. When the electronic device acquires the reference identification information, if the hand of the user of the electronic device is in a static state, the second behavior information acquired by the electronic device can further comprise hand static state information in different time periods, the hand static state information is used for representing that the hand of the user is in a static state, the hand of the user does not swing, at the moment, if the electronic device judges that the hand swing amplitude does not exist in the lower scale time period, the electronic device can also match the hand static state information in the lower scale time period with the hand static state information in different time periods to generate a sub-confidence corresponding to the hand swing amplitude of the lower scale, specifically, the electronic device judges whether the hand static state information exists in the lower scale time period according to the hand static state information in different time periods, if the hand static state information exists in the lower scale time period, the hand of the user is indicated to be in the static state without swinging, the second sub-confidence is determined to be in a non-confidence, and the sub-confidence corresponding to the hand swing amplitude of the lower scale is 0; if it is judged that the hand rest state information does not exist in the lower scale time period, and because the hand swing amplitude does not exist in the lower scale time period under the condition, the electronic equipment cannot determine whether the hand of the user is in the rest state or the hand swing state in the lower scale time period, the second sub-confidence degree is determined to be the uncertain confidence degree, and the sub-confidence degree corresponding to the hand swing amplitude of the lower scale is 0.

The electronic device matches the first upper scale locking time and the second upper scale locking time to generate a sub confidence coefficient corresponding to the upper scale locking time. As shown in table 1 above, the electronic device may preset a plurality of different lock threshold ranges, which correspond to different confidence levels. For example, three lock threshold ranges may be preset, including a first lock threshold range, a second lock threshold range, and a third lock threshold range. The electronic equipment calculates the difference value between the first locking time length and the second locking time length, inquires out the locking threshold range where the difference value is located, and determines the confidence coefficient corresponding to the locking threshold range where the difference value is found out as the sub-confidence coefficient corresponding to the locking time length. If the electronic device inquires that the locking threshold range in which the difference value is located is a first locking threshold range, and when the confidence coefficient corresponding to the first locking threshold range is the confidence coefficient, determining that the sub-confidence coefficient corresponding to the locking duration is the confidence coefficient, for example, the sub-confidence coefficient corresponding to the locking duration is 0.6; if the electronic device inquires that the locking threshold range in which the difference value is located is a second locking threshold range, and when the confidence coefficient corresponding to the second locking threshold range is the uncertain confidence coefficient, determining that the sub-confidence coefficient corresponding to the locking duration is the uncertain confidence coefficient, for example, the sub-confidence coefficient corresponding to the locking duration is 0; if the electronic device inquires that the locking threshold range in which the difference value is located is a third locking threshold range, and if the confidence coefficient corresponding to the third locking threshold range is not in accordance with the confidence coefficient, determining that the sub-confidence coefficient corresponding to the locking duration is not in accordance with the confidence coefficient, for example, the sub-confidence coefficient corresponding to the locking duration is-0.6.

The electronic device matches the first measurement duration with the second measurement duration to generate a sub-confidence corresponding to the measurement duration. As shown in table 1 above, the electronic device may preset a plurality of different measurement threshold ranges, which correspond to different confidence levels. For example, three measurement threshold ranges may be preset, including a first measurement threshold range, a second measurement threshold range, and a third measurement threshold range. The electronic equipment calculates the difference value between the first measurement time length and the second measurement time length, inquires out the measurement threshold range where the difference value is located, and determines the confidence coefficient corresponding to the measurement threshold range where the inquired difference value is located as the sub-confidence coefficient corresponding to the measurement time length. If the electronic device inquires that the measurement threshold range in which the difference value is located is a first measurement threshold range, and when the confidence coefficient corresponding to the first measurement threshold range is the coincidence confidence coefficient, determining that the sub-confidence coefficient corresponding to the measurement duration is the coincidence confidence coefficient, for example, the sub-confidence coefficient corresponding to the measurement duration is 0.6; if the electronic device inquires that the measurement threshold range in which the difference value is located is a second measurement threshold range, and when the confidence coefficient corresponding to the second measurement threshold range is the uncertain confidence coefficient, determining that the sub-confidence coefficient corresponding to the measurement duration is the uncertain confidence coefficient, for example, determining that the sub-confidence coefficient corresponding to the measurement duration is 0; if the electronic device inquires that the measurement threshold range in which the difference value is located is a third measurement threshold range, and when the confidence coefficient corresponding to the third measurement threshold range is not in accordance with the confidence coefficient, determining that the sub-confidence coefficient corresponding to the measurement duration is not in accordance with the confidence coefficient, for example, the sub-confidence coefficient corresponding to the measurement duration is-0.6.

The electronic device matches the first body weight and the second body weight to generate sub-confidence of the body weight correspondence. As shown in table 1 above, the electronic device may preset a plurality of different weight threshold ranges, which correspond to different confidence levels. For example, three body weight threshold ranges may be preset, including a first body weight threshold range, a second body weight threshold range, and a third body weight threshold range. The electronic device calculates the difference between the first weight and the second weight, queries a weight threshold range in which the difference is located, and determines the confidence corresponding to the weight threshold range in which the difference is queried as the sub-confidence corresponding to the weight. If the electronic device inquires that the weight threshold range in which the difference value is located is a first weight threshold range, and when the confidence coefficient corresponding to the first weight threshold range is the confidence coefficient, determining that the sub-confidence coefficient corresponding to the weight is the confidence coefficient, for example, the sub-confidence coefficient corresponding to the weight is 0.6; if the electronic device inquires that the weight threshold range in which the difference value is located is a second weight threshold range, and when the confidence coefficient corresponding to the second weight threshold range is an uncertain confidence coefficient, determining that the sub-confidence coefficient corresponding to the weight is an uncertain confidence coefficient, for example, the sub-confidence coefficient corresponding to the weight is 0; if the electronic device queries that the weight threshold range in which the difference value is located is a third weight threshold range, and if the confidence coefficient corresponding to the third weight threshold range is not in accordance with the confidence coefficient, determining that the sub-confidence coefficient corresponding to the weight is not in accordance with the confidence coefficient, for example, the sub-confidence coefficient corresponding to the weight is 0.

The electronic device matches the first heart rate with the second heart rate to generate a sub-confidence corresponding to the heart rate. As shown in table 1 above, the electronic device may preset a plurality of different heart rate threshold ranges, which correspond to different confidence levels. For example, three heart rate threshold ranges may be preset, including a first heart rate threshold range, a second heart rate threshold range, and a third heart rate threshold range. The electronic device calculates the difference between the first heart rate and the second heart rate, queries the heart rate threshold range in which the difference is located, and determines the confidence coefficient corresponding to the heart rate threshold range in which the queried difference is located as the sub-confidence coefficient corresponding to the heart rate. If the heart rate threshold range where the difference value is found to be the first heart rate threshold range, and the confidence coefficient corresponding to the first heart rate threshold range is the confidence coefficient, the electronic device determines that the sub-confidence coefficient corresponding to the heart rate is the confidence coefficient, for example, the sub-confidence coefficient corresponding to the heart rate is 0.6; if the heart rate threshold range where the difference value is found to be the second heart rate threshold range, and the confidence coefficient corresponding to the second heart rate threshold range is the uncertain confidence coefficient, the electronic device determines that the sub-confidence coefficient corresponding to the heart rate is the uncertain confidence coefficient, for example, the sub-confidence coefficient corresponding to the heart rate is 0; if the electronic device inquires that the heart rate threshold range in which the difference value is located is a third heart rate threshold range, and if the confidence coefficient corresponding to the third heart rate threshold range is not in accordance with the confidence coefficient, determining that the sub-confidence coefficient corresponding to the heart rate is not in accordance with the confidence coefficient, for example, the sub-confidence coefficient corresponding to the heart rate is 0.

And the electronic equipment judges the distance between the user of the electronic equipment and the body fat scale through the measured distance so as to generate a sub confidence corresponding to the measured distance. As shown in table 1 above, the electronic device may preset a plurality of different distance threshold ranges, with the different distance threshold ranges corresponding to different confidence levels. For example, three distance threshold ranges may be preset, including a first distance threshold range, a second distance threshold range, and a third distance threshold range. The electronic device queries a distance threshold range in which the measured distance is located, and determines the confidence coefficient corresponding to the distance threshold range in which the queried difference value is located as a sub-confidence coefficient corresponding to the distance. If the electronic device inquires that the distance threshold range in which the difference value is located is a first distance threshold range, and when the confidence coefficient corresponding to the first distance threshold range is the coincidence confidence coefficient, determining that the sub-confidence coefficient corresponding to the measurement distance is the coincidence confidence coefficient, for example, determining that the sub-confidence coefficient corresponding to the measurement distance is 0.6; if the electronic device queries that the distance threshold range in which the difference value is located is a second distance threshold range, and when the confidence coefficient corresponding to the second distance threshold range is the uncertain confidence coefficient, determining that the sub-confidence coefficient corresponding to the measured distance is the uncertain confidence coefficient, for example, determining that the sub-confidence coefficient corresponding to the measured distance is 0; if the heart rate threshold range where the measurement distance is located is queried to be a third distance threshold range, and the confidence coefficient corresponding to the third distance threshold range is not in accordance with the confidence coefficient, the electronic device determines that the sub-confidence coefficient corresponding to the measurement distance is not in accordance with the confidence coefficient, for example, the sub-confidence coefficient corresponding to the measurement distance is-0.6. The greater the sub-confidence corresponding to the measurement distance, the greater the probability that the user of the electronic device is judged to be the user to be measured.

The electronic device matches the foot swing amplitude of the upper scale time period with the foot swing amplitude of the different time periods to generate the sub-confidence corresponding to the foot swing amplitude of the upper scale. The electronic equipment judges whether the foot swing amplitude exists in the upper scale time period according to the foot swing amplitudes of different time periods, and if the foot swing amplitude exists in the upper scale time period, the electronic equipment determines that the sub-confidence coefficient corresponding to the foot swing amplitude of the upper scale is the first sub-confidence coefficient, wherein the indication that the corresponding foot swing amplitude can be matched in the upper scale time period. If the electronic equipment judges that the foot swing amplitude does not exist in the upper scale time period, and the electronic equipment indicates that the upper scale time period cannot be matched with the corresponding foot swing amplitude, the sub-confidence degree corresponding to the foot swing amplitude of the upper scale is determined to be the second sub-confidence degree. As shown in table 1 above, for example, if the first sub-confidence is the confidence, the sub-confidence corresponding to the foot swing amplitude of the upper scale is 0.2. For example, if the second sub-confidence includes a non-conforming confidence or an uncertain confidence, the electronic device may further identify the second sub-confidence. When the electronic device acquires the reference identification information, if the foot of the user of the electronic device is in a static state, the second behavior information acquired by the electronic device can further comprise foot static state information in different time periods, the foot static state information is used for representing that the foot of the user is in a static state, the foot of the user does not have foot swing motion, at the moment, if the electronic device judges that the foot swing amplitude does not exist in the upper scale time period, the electronic device can also match the foot static state information in the upper scale time period with the foot static state information in different time periods to generate a sub-confidence corresponding to the foot swing amplitude of the upper scale, specifically, the electronic device judges whether the foot static state information exists in the upper scale time period according to the foot static state information in different time periods, if the foot static state information is judged to exist in the upper scale time period, the foot of the user does not have foot swing motion and is in a static state, the second sub-confidence is determined to be not in accordance with the confidence, and the sub-confidence corresponding to the foot swing amplitude of the upper scale is 0; if it is determined that the foot rest state information does not exist in the upper scale time period, because the foot swing amplitude does not exist in the upper scale time period under the condition, the electronic equipment cannot determine whether the foot of the user is in the rest state or the foot swing state in the upper scale time period, the second sub-confidence degree is determined to be the uncertain confidence degree, and the sub-confidence degree corresponding to the foot swing amplitude of the upper scale is 0.

The electronic device matches the foot swing amplitude of the lower scale time period with the foot swing amplitude of the different time periods to generate the sub-confidence corresponding to the foot swing amplitude of the lower scale. The electronic equipment judges whether the foot swing amplitude exists in the lower scale time period according to the foot swing amplitudes of different time periods, and if the foot swing amplitude exists in the lower scale time period, the electronic equipment determines that the sub-confidence coefficient corresponding to the foot swing amplitude of the lower scale is the first sub-confidence coefficient, wherein the indication that the corresponding foot swing amplitude can be matched in the lower scale time period. If the electronic equipment judges that the foot swing amplitude does not exist in the lower scale time period, and the electronic equipment indicates that the lower scale time period cannot be matched with the corresponding foot swing amplitude, the sub-confidence degree corresponding to the foot swing amplitude of the lower scale is determined to be the second sub-confidence degree. As shown in table 1 above, for example, if the first sub-confidence is the confidence, the sub-confidence corresponding to the foot swing amplitude of the lower scale is 0.6. For example, if the second sub-confidence includes a non-conforming confidence or an uncertain confidence, the electronic device may further identify the second sub-confidence. When the electronic device acquires the reference identification information, if the foot of the user of the electronic device is in a static state, the second behavior information acquired by the electronic device can further comprise foot static state information in different time periods, the foot static state information is used for representing that the foot of the user is in a static state, the foot of the user does not have foot swing motion, at the moment, if the electronic device judges that the foot swing amplitude does not exist in the lower scale time period, the electronic device can also match the foot static state information in the lower scale time period with the foot static state information in different time periods to generate a sub-confidence corresponding to the foot swing amplitude of the lower scale, specifically, the electronic device judges whether the foot static state information exists in the lower scale time period according to the foot static state information in different time periods, if the foot static state information exists in the lower scale time period, the foot static state information indicates that the foot of the user does not swing motion and is in the static state in the lower scale time, the second sub-confidence is determined to be not in accordance with the confidence, and the sub-confidence corresponding to the foot swing amplitude of the lower scale is 0; if it is determined that the foot rest state information does not exist in the lower scale time period, and because the foot swing amplitude does not exist in the lower scale time period under the condition, the electronic equipment cannot determine whether the foot of the user is in the rest state or the foot swing state in the lower scale time period, the second sub-confidence degree is determined to be the uncertain confidence degree, and the sub-confidence degree corresponding to the foot swing amplitude of the lower scale is 0.

Step 216, the body fat scale obtains a matching result from at least one electronic device.

And step 218, the body fat scale judges whether the user of the electronic equipment is a tested user according to the matching result of at least one electronic equipment.

In the embodiment of the invention, if the matching result is the confidence coefficient and the body fat scale receives the confidence coefficients of a plurality of electronic devices, the electronic devices screen the confidence coefficient larger than the set threshold value from the confidence coefficients of the plurality of electronic devices, determine the maximum confidence coefficient from the confidence coefficients larger than the set threshold value, and judge the user of the electronic device corresponding to the maximum confidence coefficient as the tested user.

In this embodiment, if the matching result is the confidence coefficient, and the body fat scale receives the confidence coefficient of an electronic device, if the electronic device determines that the confidence coefficient of the electronic device is greater than the set threshold, the electronic device determines that the user of the electronic device corresponding to the confidence coefficient is the tested user.

In this embodiment, for example, the user of the handheld mobile phone is determined as the user to be tested, the body fat scale is linked with the mobile phone, and the user of the handheld mobile phone is identified as the user to be tested, so that the accuracy of user identification is improved.

In the following, a workflow of a user identification method is illustrated by another specific embodiment, for example, this embodiment shows a scenario where a body fat scale cooperates with a smart watch, in which a measured user wears the smart watch (or smart bracelet) on his wrist, and stands on the body fat scale to measure, and the body fat scale cooperates with the smart watch (or smart bracelet) to identify the measured user. Fig. 7 is a flowchart of a user identification method in other embodiments, as shown in fig. 7, where the electronic device may be a smart watch (or smart bracelet), the method includes:

step 302, the body fat scale obtains measurement information of a measured user, wherein the measurement information of the measured user comprises first behavior information and first sign data, and the first behavior information is used for representing measurement behaviors of the measured user detected when the body fat scale measures the sign data of the measured user.

Step 304, the electronic device obtains identification reference information of the user of the electronic device, where the identification reference information includes second behavior information and second sign data, and the second behavior information is used to characterize a behavior of the user of the electronic device.

In this embodiment, step 302 and step 304 are two independently executable steps, for example, step 302 may be performed before step 304, or step 304 may be performed before step 302, or step 302 and step 304 may be performed simultaneously.

Step 306, the electronic device receives the identification instruction broadcast by the body fat scale.

Step 308, the electronic device calculates a measurement distance according to the RSSI of the identification instruction, wherein the measurement distance is the distance between the electronic device and the body fat scale.

Step 310, the electronic device broadcasts a plurality of data requests in response to the identification instruction, and receives first behavior information and first characterization data broadcast by the body fat scale in response to the plurality of data requests.

The electronic device can acquire the first behavior information and the first sign data from the body fat scale according to a preset cooperative behavior mode. In this embodiment, the cooperative behavior mode is used to indicate that the electronic device needs to obtain the first behavior information from the body fat scale and the first weight and the first heart rate in the first sign data, and the step 310 may include: the electronic equipment broadcasts a behavior information data request and receives first behavior information broadcast by the body fat scale in response to the behavior information data request; the electronic equipment broadcasts a weight data request and receives a first weight which is broadcasted by the body fat scale in response to the weight data request; the electronic device broadcasts a heart rate data request and receives a first heart rate broadcast by the body fat scale in response to the heart rate data request.

Step 312, the electronic device detects that the electronic device is worn on the wrist of the user according to the user wearing behavior.

For example, if the electronic device detects that the electronic device is worn on the wrist of the user, step 314 is performed.

For example, if the electronic device detects that the electronic device is not worn on the wrist of the user and is not worn on the foot of the user, indicating that the user is not wearing a smart band, then the following steps 314 to 316 are not performed.

Step 314, the electronic device generates a matching result according to the measurement information and the identification reference information, where the matching result is used to characterize the probability that the user of the electronic device is the tested user.

In this embodiment, the first behavior information includes a scale loading time period, a first scale loading locking time period, a first measurement time period, and a scale unloading time period, the first sign data includes a first weight and a first heart rate, the second behavior information includes hand swing amplitudes of different time periods, a second scale loading time period, and a second measurement time period, and the second sign data includes a second weight and a second heart rate. As an alternative, the identification reference information further comprises a measured distance.

In this embodiment, the matching result includes a confidence level. The electronic device matches the hand swing amplitude of the upper scale with the hand swing amplitude of the different time periods to generate a sub-confidence corresponding to the hand swing amplitude of the upper scale, the electronic device matches the hand swing amplitude of the lower scale with the hand swing amplitude of the different time periods to generate a sub-confidence corresponding to the hand swing amplitude of the lower scale, the electronic device matches the first upper scale locking time length and the second upper scale locking time length to generate a sub-confidence corresponding to the upper scale locking time length, the electronic device matches the first measuring time length and the second measuring time length to generate a sub-confidence corresponding to the measuring time length, the electronic device matches the first body weight and the second body weight to generate a sub-confidence corresponding to the body weight, and the electronic device judges the distance between a user of the electronic device and the body fat scale through the measuring distance to generate a sub-confidence corresponding to the measuring distance. The electronic equipment performs weighted summation calculation or weighted average calculation on the sub-confidence coefficient corresponding to the hand swing amplitude of the upper scale, the sub-confidence coefficient corresponding to the hand swing amplitude of the lower scale, the sub-confidence coefficient corresponding to the locking time of the upper scale, the sub-confidence coefficient corresponding to the measuring time, the sub-confidence coefficient corresponding to the weight, the sub-confidence coefficient corresponding to the heart rate and the sub-confidence coefficient corresponding to the measuring distance, and generates the confidence coefficient. The weights corresponding to different sub-confidences may be set, for example, the weight corresponding to the sub-confidence corresponding to the hand swing amplitude of the upper scale and the weight corresponding to the sub-confidence corresponding to the hand swing amplitude of the lower scale may be set to be greater than the weights corresponding to other sub-confidences.

A detailed description of step 314 may be referred to the description of step 214, and will not be repeated here.

Step 316, the body fat scale obtains a matching result from at least one electronic device.

And step 318, judging whether the user of the electronic equipment is a tested user or not according to the matching result of at least one electronic equipment by the body fat scale.

In this embodiment, for example, a user wearing the smart watch is determined as a measured user, the body fat scale is linked with the smart watch, and the user wearing the smart watch on the wrist is identified as the measured user, so that the accuracy of user identification is improved. Because the intelligent watch is worn on the wrist of the user, compared with a hand-held mobile phone of the user, the intelligent watch can more accurately measure the hand swing amplitude of the user, and therefore the accuracy of user identification can be further improved.

In the following, a workflow of a user identification method is illustrated by another specific embodiment, for example, this embodiment shows a scenario where a body fat scale and an intelligent bracelet cooperate, in which a user to be tested wears the intelligent bracelet on his foot, stands on the body fat scale to measure, and links the body fat scale and the intelligent bracelet to identify the user to be tested. FIG. 8 is a flowchart of a user identification method in other embodiments, as shown in FIG. 8, where the electronic device may be a smart bracelet, the method includes:

step 402, the body fat scale obtains measurement information of a measured user, wherein the measurement information of the user at the measured side comprises first behavior information and first sign data, and the first behavior information is used for representing measurement behaviors of the measured user detected when the body fat scale measures the sign data of the measured user.

Step 404, the electronic device obtains identification reference information of a user of the electronic device, where the identification reference information includes second behavior information and second sign data, and the second behavior information is used to characterize a behavior of the user of the electronic device.

In this embodiment, step 402 and step 404 are two independently executable steps, for example, step 402 may be performed before step 404, or step 404 may be performed before step 402, or step 402 and step 404 may be performed simultaneously.

Step 406, the electronic device receives the identification instruction broadcast by the body fat scale.

Step 408, the electronic device calculates a measurement distance according to the RSSI of the identification command, where the measurement distance is a distance between the electronic device and the body fat scale.

In step 410, the electronic device broadcasts a plurality of data requests in response to the identification instruction, and receives first behavior information and first characterization data broadcast by the body fat scale in response to the plurality of data requests.

The electronic device can acquire the first behavior information and the first sign data from the body fat scale according to a preset cooperative behavior mode. In this embodiment, the cooperative behavior mode is used to indicate that the electronic device needs to obtain the first behavior information from the body fat scale and the first weight and the first heart rate in the first sign data, and the step 410 may include: the electronic equipment broadcasts a behavior information data request and receives first behavior information broadcast by the body fat scale in response to the behavior information data request; the electronic equipment broadcasts a weight data request and the body fat scale responds to the first weight broadcasted by the weight data request; the electronic device broadcasts a heart rate data request and receives a first heart rate broadcast by the body fat scale in response to the heart rate data request.

Step 412, the electronic device detects that the electronic device is worn on the foot of the user according to the user wearing behavior.

For example, if the electronic device detects that the electronic device is worn on the foot of the user, step 414 is performed.

For example, if the electronic device detects that the electronic device is not worn on the user's foot and not on the user's wrist, indicating that the user is not wearing a smart band, then the following steps 414 to 416 are not performed.

In step 414, the electronic device generates a matching result according to the measurement information and the identification reference information, where the matching result is used to characterize the probability that the user of the electronic device is the tested user.

In this embodiment, the first behavior information includes a loading time period, a first loading locking time period, a first measurement time period, and a unloading time period, the first sign data includes a first weight and a first heart rate, the second behavior information includes a foot swing amplitude, a second loading time period, and a second measurement time period for different time periods, and the second sign data includes a second weight and a second heart rate. As an alternative, the identification reference information further comprises a measured distance.

In this embodiment, the matching result includes a confidence level. The electronic device matches the foot swing amplitude of the upper scale with the foot swing amplitude of the different time periods to generate the sub-confidence corresponding to the foot swing amplitude of the upper scale, the electronic device matches the foot swing amplitude of the lower scale with the foot swing amplitude of the different time periods to generate the sub-confidence corresponding to the foot swing amplitude of the lower scale, the electronic device matches the first upper scale locking time length and the second upper scale locking time length to generate the sub-confidence corresponding to the upper scale locking time length, the electronic device matches the first measuring time length and the second measuring time length to generate the sub-confidence corresponding to the measuring time length, the electronic device matches the first body weight and the second body weight to generate the sub-confidence corresponding to the body weight, and the electronic device judges the distance between a user of the electronic device and the body fat scale through the measuring distance to generate the sub-confidence corresponding to the measuring distance. The electronic equipment performs weighted summation calculation or weighted average calculation on the sub-confidence coefficient corresponding to the foot swing amplitude of the upper scale, the sub-confidence coefficient corresponding to the foot swing amplitude of the lower scale, the sub-confidence coefficient corresponding to the locking time of the upper scale, the sub-confidence coefficient corresponding to the measuring time, the sub-confidence coefficient corresponding to the weight, the sub-confidence coefficient corresponding to the heart rate and the sub-confidence coefficient corresponding to the measuring distance, and generates the confidence coefficient. The weights corresponding to different sub-confidences may be set, for example, the weight corresponding to the sub-confidence corresponding to the foot swing amplitude of the upper scale and the weight corresponding to the sub-confidence corresponding to the foot swing amplitude of the lower scale may be set to be greater than the weights corresponding to other sub-confidences.

A detailed description of step 414 may be referred to the description of step 214, and will not be repeated here.

Step 416, the body fat scale obtains a matching result from at least one electronic device.

And 418, judging whether the user of the electronic equipment is a tested user or not by the body fat scale according to the matching result of at least one electronic equipment.

In this embodiment, if the matching result is the confidence coefficient, and the body fat scale receives the confidence coefficient of an electronic device, if the electronic device determines that the confidence coefficient of the electronic device is greater than the set threshold, the electronic device determines that the user of the electronic device corresponding to the confidence coefficient is the tested user. In this embodiment, for example, a user wearing the smart bracelet is determined as a measured user, the body fat scale is linked with the smart bracelet, and the user wearing the smart bracelet on the foot is identified as the measured user, so that the accuracy of user identification is improved. Because the intelligent bracelet is worn on the feet of the user, compared with a handheld mobile phone of the user, the intelligent bracelet can more accurately measure the swing amplitude of the feet of the user, and therefore the accuracy of user identification can be further improved.

The embodiment of the invention provides electronic equipment which can be terminal equipment or circuit equipment built in the terminal equipment. The electronic device includes: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the electronic device, enable the electronic device to perform the various steps of the user identification method embodiments described above.

The embodiment of the invention provides a body fat scale, which can be terminal equipment or circuit equipment built in the terminal equipment. The body fat scale comprises: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the body fat scale, enable the body fat scale to be used to perform the various steps in the user identification method embodiments described above.

Embodiments of the present invention provide a computer readable storage medium having instructions stored therein which, when executed on a computer, cause the computer to perform the steps of the user identification method embodiments described above.

Embodiments of the present invention provide a computer program product comprising instructions which, when run on a computer or on any of at least one processor, cause the computer to perform the steps of the user identification method embodiments described above.

In the embodiments of the present invention, "at least one" means one or more, and "a plurality" means two or more. "and/or", describes an association relation of association objects, and indicates that there may be three kinds of relations, for example, a and/or B, and may indicate that a alone exists, a and B together, and B alone exists. Wherein A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of the following" and the like means any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.

Those of ordinary skill in the art will appreciate that the various elements and algorithm steps described in the embodiments disclosed herein can be implemented as a combination of electronic hardware, computer software, and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In several embodiments provided by the present invention, any of the functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely exemplary embodiments of the present invention, and any person skilled in the art may easily conceive of changes or substitutions within the technical scope of the present invention, which should be covered by the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A user identification method, characterized in that the method is applied to a body fat scale and at least one electronic device, and communication between the body fat scale and the at least one electronic device is based on a short-distance wireless communication protocol;

the method comprises the following steps:

2. The method of claim 1, wherein the electronic device generating a matching result from the measurement information and the identification reference information comprises:

3. The method of claim 1, wherein the measurement information further includes first sign data obtained by the body fat scale measuring the measured user, the identification reference information further includes second sign data, and the electronic device generates a matching result according to the measurement information and the identification reference information, including:

4. The method of claim 1, wherein the measurement information further comprises first sign data obtained by the body fat scale measuring the measured user, the identification reference information further comprises second sign data and a measurement distance, and the measurement distance is a distance between the electronic device and the body fat scale;

5. The method of any one of claims 1 to 4, wherein the first behavioral information includes at least one of a scale up period, a first scale up lock period, a first measurement period, or a scale down period.

6. The method of any one of claims 1 to 5, wherein the second behavior information includes at least one of a hand swing amplitude corresponding to a different time period, a foot swing amplitude corresponding to a different time period, a second load lock duration, or a second measurement duration, wherein the second load lock duration is a load lock duration of a user stored by the electronic device, and the second measurement duration is a measurement duration of the user stored by the electronic device.

7. The method of any one of claims 3 to 6, wherein the first sign data comprises at least one of a first body weight, a first heart rate, or a first body fat rate.

8. The method of any of claims 3 to 7, wherein the second characterization data comprises at least one of a second weight, a second heart rate, or a second body fat rate, wherein the second weight is a weight of the user stored by the electronic device, the second heart rate is a heart rate measured by the electronic device for the user of the electronic device, and the second body fat rate is a body fat rate of the user stored by the electronic device.

9. The method of claim 1, wherein the measurement information further includes first sign data obtained from measurements of the user under test by the body fat scale;

10. The method of claim 1, wherein the measurement information further includes first sign data obtained from measurements of the user under test by the body fat scale;

11. The method according to claim 9 or 10, wherein the identification reference information further comprises a measured distance, the measured distance being a distance between the electronic device and the body fat scale; after receiving the identification instruction broadcast by the body fat scale, the electronic equipment further comprises:

12. The method of claim 1, wherein the identification reference information further comprises a measured distance, the measured distance being a distance between the electronic device and the body fat scale, the electronic device comprising a cell phone, a smart bracelet, or a smart watch;

the method further comprises the steps of:

13. The method according to any one of claims 1 to 11, wherein the electronic device is a smart bracelet or a smart watch;

The method further comprises the steps of:

14. The method of any one of claims 1 to 13, wherein the matching result is a confidence level.

15. The user identification method is characterized by being applied to electronic equipment, wherein the electronic equipment and the body fat scale are communicated based on a short-distance wireless communication protocol;

the method comprises the following steps:

16. The method of claim 15, wherein the electronic device generating a matching result from the measurement information and the identification reference information comprises:

17. The method according to claim 15 or 16, wherein the measurement information further includes first sign data obtained by the body fat scale measuring the measured user, the identification reference information further includes second sign data, and the electronic device generates a matching result according to the measurement information and the identification reference information, including:

18. The method according to any one of claims 15 to 17, wherein the measurement information further includes first characteristic data obtained by the body fat scale measuring the measured user, the identification reference information further includes second characteristic data and a measurement distance, and the measurement distance is a distance between the electronic device and the body fat scale;

19. A user identification method, characterized in that the method is applied to a body fat scale, and the body fat scale and the at least one electronic device are communicated based on a short-distance wireless communication protocol;

the method comprises the following steps:

20. The method of claim 19, wherein the measurement information further includes first characterization data measured by the body fat scale for the user under test;

21. The method of claim 19 or 20, wherein the measurement information further includes first sign data obtained by the body fat scale measuring the measured user;

22. An electronic device, comprising: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions, which when executed by the electronic device, cause the electronic device to perform the user identification method of any of claims 15-18.

23. A body fat scale, comprising: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the body fat scale, cause the body fat scale to perform the user identification method of any one of claims 19 to 21.

24. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program, when run, controls a device in which the computer-readable storage medium is located to perform the user identification method of any one of claims 15 to 18 or to perform the user identification method of any one of claims 19 to 21.

25. A computer program product comprising instructions which, when run on a computer or any of the at least one processors, cause the computer to perform the user identification method of any of claims 15 to 18 or to perform the user identification method of any of claims 19 to 21.